Rapidly expanding information archives provide access to terabytes of electronic data, e.g., electronic museums, electronic newspapers, musical archives, digital libraries, software archives, mailing lists, up-to-date weather information and geographic data. Consequently, current advances in information technology are driven by the need to increase the effectiveness of information access and retrieval.
Traditionally, information providers try to overcome the inadequacies of information retrieval by providing fast and powerful search engines, see, for example, U.S. Pat. No. 5,293,552 (PHN 13,666) herewith incorporated by reference. Retrieval mechanisms based on keywords typically return a large set of documents, but are not very precise in their return. Examples of searching systems are commonly available search engines, databases and library lookup systems. The user interacts with the system by providing a query with sufficient information and gets back a set of documents that more or less match the query.
Traditional approaches have devised mechanisms to map a user's query to a document based on overlapping terms or concept words between the query and the document terms.
One known approach is known from "Experiments on Using Semantic Distances Between Words in Image Caption Retrieval", Alan F. Smeaton and Ian Quigley, Proceedings of the 19th Annual International A CM SIGIR Conference on Research and Development in Information Retrieval, August 1996, Zurich, Switzerland. This approach uses a quantitative measure of semantic similarity between index terms for queries and documents.
Another recent method is described in "A Deductive Data Model for Query Expansion", Kalervo Jarvelin, Jaana Kristensen, Timo Niemi, Eero Sormunen and Heikki Keskustalo, Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, August 1996, Zurich, Switzerland. This method introduces concept-based query expansion, where each concept is expanded to a disjunctive set of concepts on the basis of conceptual relationships pointed out by the user.
Yet another known idea is proposed in "Incremental Relevance Feedback for Information Filtering", James Allan, Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. August 1996, Zurich, Switzerland. This idea relates to relevance feedback techniques that process shifts in user interest patterns over a period of time. The user feeds back notions of which query results he/she believes are relevant to the current query.